The ASSESS-AKI Study found urinary epidermal growth factor is associated with reduced risk of major adverse kidney events
Authors: Steven Menez, Yumeng Wen, Leyuan Xu, Dennis G. Moledina, Heather Thiessen-Philbrook, David Hu, Wassim Obeid, Pavan K. Bhatraju, T. Alp Ikizler, Edward D. Siew, Vernon M. Chinchilli, Amit X. Garg, Alan S. Go, Kathleen D. Liu, James S. Kaufman, Paul L. Kimmel, Jonathan Himmelfarb, Steven G. Coca, Lloyd G. Cantley, Chirag R. Parikh
Journal: Kidney International (2023)

Biomarkers of tubular function such as epidermal growth factor (EGF) may improve prognostication of participants at highest risk for chronic kidney disease (CKD) after hospitalization. To examine this, we measured urinary EGF (uEGF) from samples collected in the Assessment, Serial Evaluation, and Subsequent Sequelae of Acute Kidney Injury (ASSESS-AKI) Study, a multi-center, prospective, observational cohort of hospitalized participants with and without AKI. Cox proportional hazards regression was used to investigate the association of uEGF/Cr at hospitalization, three months post-discharge, and the change between these time points with major adverse kidney events (MAKE): CKD incidence, progression, or development of kidney failure. Clinical findings were paired with mechanistic studies comparing relative Egf expression in mouse models of kidney atrophy or repair after ischemia-reperfusion injury. MAKE was observed in 20% of 1,509 participants over 4.3 years of follow-up. Each 2-fold higher level of uEGF/Cr at three months was associated with decreased risk of MAKE (adjusted hazards ratio 0.46, 95% confidence interval: 0.39-0.55). Participants with the highest increase in uEGF/Cr from hospitalization to three-month follow-up had a lower risk of MAKE (adjusted hazards ratio 0.52; 95% confidence interval: 0.36-0.74) compared to those with the least change in uEGF/Cr. A model using uEGF/Cr at three months combined with clinical variables yielded moderate discrimination for MAKE (area under the curve 0.73; 95% confidence interval: 0.69-0.77) and strong discrimination for kidney failure at four years (area under the curve 0.96; 95% confidence interval: 0.92-1.00). Accelerated restoration of Egf expression in mice was seen in the model of adaptive repair after injury, compared to a model of progressive atrophy. Thus, urinary EGF/Cr may be a biomarker of distal tubular health, with higher concentrations and increased uEGF/Cr post-discharge independently associated with reduced risk of MAKE in hospitalized patients. Biomarkers of tubular function such as epidermal growth factor (EGF) may improve prognostication of participants at highest risk for chronic kidney disease (CKD) after hospitalization. To examine this, we measured urinary EGF (uEGF) from samples collected in the Assessment, Serial Evaluation, and Subsequent Sequelae of Acute Kidney Injury (ASSESS-AKI) Study, a multi-center, prospective, observational cohort of hospitalized participants with and without AKI. Cox proportional hazards regression was used to investigate the association of uEGF/Cr at hospitalization, three months post-discharge, and the change between these time points with major adverse kidney events (MAKE): CKD incidence, progression, or development of kidney failure. Clinical findings were paired with mechanistic studies comparing relative Egf expression in mouse models of kidney atrophy or repair after ischemia-reperfusion injury. MAKE was observed in 20% of 1,509 participants over 4.3 years of follow-up. Each 2-fold higher level of uEGF/Cr at three months was associated with decreased risk of MAKE (adjusted hazards ratio 0.46, 95% confidence interval: 0.39-0.55). Participants with the highest increase in uEGF/Cr from hospitalization to three-month follow-up had a lower risk of MAKE (adjusted hazards ratio 0.52; 95% confidence interval: 0.36-0.74) compared to those with the least change in uEGF/Cr. A model using uEGF/Cr at three months combined with clinical variables yielded moderate discrimination for MAKE (area under the curve 0.73; 95% confidence interval: 0.69-0.77) and strong discrimination for kidney failure at four years (area under the curve 0.96; 95% confidence interval: 0.92-1.00). Accelerated restoration of Egf expression in mice was seen in the model of adaptive repair after injury, compared to a model of progressive atrophy. Thus, urinary EGF/Cr may be a biomarker of distal tubular health, with higher concentrations and increased uEGF/Cr post-discharge independently associated with reduced risk of MAKE in hospitalized patients. Lay SummaryUrinary epidermal growth factor (uEGF) is a protein expressed in the distal nephron, with previous studies demonstrating that higher levels of uEGF normalized to urinary creatinine concentration (uEGF/Cr) associated with lower risk of adverse kidney outcomes after acute kidney injury. In this study, we discovered that among hospitalized adult patients, higher uEGF/Cr measured at hospitalization, higher uEGF/Cr measured at 3-month postdischarge follow-up, and an increase in uEGF/Cr between these time points were all independently associated with lower risk of major adverse kidney events (MAKEs), including chronic kidney disease incidence and progression. In prediction modeling, uEGF/Cr provided moderate discrimination to predict MAKEs and strong discrimination for end-stage kidney disease over time. Urinary epidermal growth factor (uEGF) is a protein expressed in the distal nephron, with previous studies demonstrating that higher levels of uEGF normalized to urinary creatinine concentration (uEGF/Cr) associated with lower risk of adverse kidney outcomes after acute kidney injury. In this study, we discovered that among hospitalized adult patients, higher uEGF/Cr measured at hospitalization, higher uEGF/Cr measured at 3-month postdischarge follow-up, and an increase in uEGF/Cr between these time points were all independently associated with lower risk of major adverse kidney events (MAKEs), including chronic kidney disease incidence and progression. In prediction modeling, uEGF/Cr provided moderate discrimination to predict MAKEs and strong discrimination for end-stage kidney disease over time. Evaluation of long-term health risks after an acute insult or injury remains a significant problem. Several studies have investigated the risk of long-term decline in kidney function, and the development of chronic kidney disease (CKD), after acute kidney injury (AKI).1Chawla L.S. Kimmel P.L. Acute kidney injury and chronic kidney disease: an integrated clinical syndrome.Kidney Int. 2012; 82: 516-524Abstract Full Text Full Text PDF PubMed Scopus (621) Google Scholar, 2See E.J. Jayasinghe K. Glassford N. et al.Long-term risk of adverse outcomes after acute kidney injury: a systematic review and meta-analysis of cohort studies using consensus definitions of exposure.Kidney Int. 2019; 95: 160-172Abstract Full Text Full Text PDF PubMed Scopus (239) Google Scholar, 3Horne K.L. Shardlow A. Taal M.W. et al.Long term outcomes after acute kidney injury: lessons from the ARID study.Nephron. 2015; 131: 102-106Crossref PubMed Scopus (11) Google Scholar However, clinical AKI, a known risk factor for progression to CKD,4Ikizler T.A. Parikh C.R. Himmelfarb J. et al.A prospective cohort study of acute kidney injury and kidney outcomes, cardiovascular events, and death.Kidney Int. 2021; 99: 456-465Abstract Full Text Full Text PDF PubMed Scopus (55) Google Scholar relies by definition on serum creatinine concentration (sCr) and urine output, which are both limited with regard to accuracy, timeliness, and precision in determining type and severity of injury.5Delanaye P. Cavalier E. Pottel H. Serum creatinine: not so simple.Nephron. 2017; 136: 302-308Crossref PubMed Scopus (188) Google Scholar Biomarkers of kidney injury, inflammation, and repair have therefore been increasingly investigated toward improving the accuracy and precision in the diagnosis of kidney disease.6Haase M. Kellum J.A. Ronco C. Subclinical AKI--an emerging syndrome with important consequences.Nat Rev Nephrol. 2012; 8: 735-739Crossref PubMed Scopus (177) Google Scholar,7Ronco C. Kellum J.A. Haase M. Subclinical AKI is still AKI.Crit Care. 2012; 16: 313Crossref PubMed Scopus (51) Google Scholar Similarly, biomarkers have been explored for their prognostic potential of short- and long-term adverse kidney outcomes in an episode of AKI.8Menez S. Moledina D.G. Garg A.X. et al.Results from the TRIBE-AKI Study found associations between post-operative blood biomarkers and risk of chronic kidney disease after cardiac surgery.Kidney Int. 2021; 99: 716-724Abstract Full Text Full Text PDF PubMed Scopus (26) Google Scholar, 9Menez S. Ju W. Menon R. et al.Urinary EGF and MCP-1 and risk of CKD after cardiac surgery.JCI Insight. 2021; 6e147464PubMed Google Scholar, 10Menez S. Moledina D.G. Thiessen-Philbrook H. et al.Prognostic significance of urinary biomarkers in patients hospitalized with COVID-19.Am J Kidney Dis. 2022; 79: 257-267.e1Abstract Full Text Full Text PDF PubMed Scopus (20) Google Scholar, 11Mansour S.G. Bhatraju P.K. Coca S.G. et al.Angiopoietins as prognostic markers for future kidney disease and heart failure events after acute kidney injury.J Am Soc Nephrol. 2022; 33: 613Crossref PubMed Scopus (10) Google Scholar, 12Wilson M. Packington R. Sewell H. et al.Biomarkers during recovery from AKI and prediction of long-term reductions in estimated GFR.Am J Kidney Dis. 2022; 79: 646-656.e1Abstract Full Text Full Text PDF PubMed Scopus (13) Google Scholar, 13Puthumana J. Thiessen-Philbrook H. Xu L. et al.Biomarkers of inflammation and repair in kidney disease progression.J Clin Invest. 2021; 131e139927Crossref PubMed Scopus (75) Google Scholar Epidermal growth factor (EGF) is a protein expressed in multiple tissues in the body that serves as a biomarker of repair after tissue injury.14Harris R.C. Potential physiologic roles for epidermal growth factor in the kidney.Am J Kidney Dis. 1991; 17: 627-630Abstract Full Text PDF PubMed Scopus (77) Google Scholar In the kidney, EGF serves as a marker of epithelial cell integrity in the thick ascending loop of Henle and the distal tubule.9Menez S. Ju W. Menon R. et al.Urinary EGF and MCP-1 and risk of CKD after cardiac surgery.JCI Insight. 2021; 6e147464PubMed Google Scholar,15Ju W. Nair V. Smith S. et al.Tissue transcriptome-driven identification of epidermal growth factor as a chronic kidney disease biomarker.Sci Transl Med. 2015; 7: 316ra193Crossref PubMed Scopus (265) Google Scholar We have previously demonstrated how higher levels of urinary EGF (uEGF) in various short-term clinical settings, such as cardiac surgery, and in the setting of coronavirus disease 2019 (COVID-19) are associated with lower risk of long-term adverse kidney outcomes.9Menez S. Ju W. Menon R. et al.Urinary EGF and MCP-1 and risk of CKD after cardiac surgery.JCI Insight. 2021; 6e147464PubMed Google Scholar,10Menez S. Moledina D.G. Thiessen-Philbrook H. et al.Prognostic significance of urinary biomarkers in patients hospitalized with COVID-19.Am J Kidney Dis. 2022; 79: 257-267.e1Abstract Full Text Full Text PDF PubMed Scopus (20) Google Scholar In addition, uEGF normalized to urinary creatinine concentration (uEGF/Cr) has been associated with progression of CKD in multiple chronic disorders, including diabetic kidney disease and various glomerular disorders.16Worawichawong S. Radinahamed P. Muntham D. et al.Urine epidermal growth factor, monocyte chemoattractant protein-1 or their ratio as biomarkers for interstitial fibrosis and tubular atrophy in primary glomerulonephritis.Kidney Blood Press Res. 2016; 41: 997-1007Crossref PubMed Scopus (31) Google Scholar,17Satirapoj B. Dispan R. Radinahamed P. et al.Urinary epidermal growth factor, monocyte chemoattractant protein-1 or their ratio as predictors for rapid loss of renal function in type 2 diabetic patients with diabetic kidney disease.BMC Nephrol. 2018; 19: 246Crossref PubMed Scopus (45) Google Scholar At least 1 study has investigated the association of temporal changes in uEGF/Cr with long-term outcomes in the setting of lupus nephritis,18Mejia-Vilet J.M. Shapiro J.P. Zhang X.L. et al.Association between urinary epidermal growth factor and renal prognosis in lupus nephritis.Arthritis Rheumatol. 2021; 73: 244-254Crossref PubMed Scopus (20) Google Scholar but to our knowledge, no prior study has evaluated how temporal changes in uEGF/Cr from hospitalization to the immediate postdischarge period may inform future CKD risk. In this study, we evaluated the association between uEGF/Cr measured during hospitalization and at 3 months after hospital discharge with major adverse kidney events (MAKEs) in the prospective Assessment, Serial Evaluation, and Subsequent Sequelae After AKI (ASSESS-AKI) Study. We hypothesized that uEGF/Cr at both time points would be associated with future CKD risk, and particularly that the change in uEGF/Cr from hospitalization to postdischarge follow-up would also associate with long-term CKD risk. In addition, increases in uEGF/Cr would imply recovery of distal tubular function. We also sought to complement our clinical findings with mechanistic insights into Egf expression after kidney injury through murine models of ischemia-reperfusion injury (IRI) and hypothesized that Egf expression would differ in a model of adaptive repair compared with one of atrophy after injury. The ASSESS-AKI Study is a prospective, matched cohort study of hospitalized patients who did or did not experience an episode of AKI.19Go A.S. Parikh C.R. Ikizler T.A. et al.The Assessment, Serial Evaluation, and Subsequent Sequelae of Acute Kidney Injury (ASSESS-AKI) Study: design and methods.BMC Nephrol. 2010; 11: 22Crossref PubMed Scopus (126) Google Scholar Details of the ASSESS-AKI Study have been previously published.20Hsu C.Y. Chinchilli V.M. Coca S. et al.Post-acute kidney injury proteinuria and subsequent kidney disease progression: the Assessment, Serial Evaluation, and Subsequent Sequelae in Acute Kidney Injury (ASSESS-AKI) Study.JAMA Intern Med. 2020; 180: 402-410Crossref PubMed Scopus (85) Google Scholar Briefly, a total of 1538 hospitalized adult patients were recruited between December 2009 and February 2015 across 4 clinical centers in North America, which included 769 patients who developed an episode of AKI and survived to a visit 3 months after discharge, along with 769 matched controls. For our current study, we excluded participants who had missing biomarker, clinical, or follow-up data before 3 months after hospital discharge (Supplementary Figure S1). Follow-up visits were performed at 3 and 12 months postdischarge, and annually thereafter, with a median follow-up time of 4.3 years in total. In addition to biospecimen collection, questionnaire administration, and physical measurements, interim clinical events and medication reconciliation were recorded at these in-person visits. Interim clinical events and medication reconciliation also occurred at 6-month intervals via telephone call, between annual study visits. In the ASSESS-AKI Study, blood and urine samples were collected at the time of enrollment during hospitalization and at various time points after hospital discharge, as described previously.20Hsu C.Y. Chinchilli V.M. Coca S. et al.Post-acute kidney injury proteinuria and subsequent kidney disease progression: the Assessment, Serial Evaluation, and Subsequent Sequelae in Acute Kidney Injury (ASSESS-AKI) Study.JAMA Intern Med. 2020; 180: 402-410Crossref PubMed Scopus (85) Google Scholar For our present study, the primary exposure was uEGF/Cr, based on urinary EGF and creatinine measured from samples collected at the 3-month hospital discharge follow-up. We also measured uEGF/Cr from samples obtained during hospitalization. AKI was defined using modified Kidney Disease: Improving Global Outcomes (KDIGO) criteria, with stage 1 AKI based on a relative increase in sCr concentration of 50%, or absolute increase of 0.3 mg/dl in peak sCr above baseline, as defined in the ASSESS-AKI Study protocol.19Go A.S. Parikh C.R. Ikizler T.A. et al.The Assessment, Serial Evaluation, and Subsequent Sequelae of Acute Kidney Injury (ASSESS-AKI) Study: design and methods.BMC Nephrol. 2010; 11: 22Crossref PubMed Scopus (126) Google Scholar Baseline kidney function was determined by the most recent outpatient, non–emergency department sCr measurement between 7 and 365 days before index hospitalization; estimated glomerular filtration rate (eGFR) was calculated using the CKD Epidemiology Collaboration equation.19Go A.S. Parikh C.R. Ikizler T.A. et al.The Assessment, Serial Evaluation, and Subsequent Sequelae of Acute Kidney Injury (ASSESS-AKI) Study: design and methods.BMC Nephrol. 2010; 11: 22Crossref PubMed Scopus (126) Google Scholar,21Levey A.S. Stevens L.A. Schmid C.H. et al.A new equation to estimate glomerular filtration rate.Ann Intern Med. 2009; 150: 604-612Crossref PubMed Scopus (17936) Google Scholar Participant age, sex (male or female), race, ethnicity, and smoking status were obtained during index hospitalization (Supplementary Table S1). Baseline CKD, defined by a baseline eGFR <60 ml/min per 1.73 m2 by the CKD Epidemiology Collaboration equation at the time of study enrollment,21Levey A.S. Stevens L.A. Schmid C.H. et al.A new equation to estimate glomerular filtration rate.Ann Intern Med. 2009; 150: 604-612Crossref PubMed Scopus (17936) Google Scholar diabetes mellitus status, as well as the development of AKI and sepsis during hospitalization were recorded for each participant. In addition to uEGF/Cr, urinary biomarkers measured at both the hospitalization and 3-month postdischarge follow-up included the following: creatinine, albumin, chitinase 3–like protein 1, interleukin-18, kidney injury molecule-1, monocyte chemoattractant protein-1, neutrophil gelatinase-associated lipocalin, and uromodulin. Body mass index (BMI) was calculated on the basis of height and weight measured at 3-month follow-up. After urine collection, samples were centrifuged, with supernatant aliquoted and stored at –80 ºC until biomarkers were measured. Urinary creatinine concentration was measured using the Roche enzymatic method (Roche Diagnostics). All other urinary biomarkers were measured on the Meso Scale Discovery platform. The Meso Scale Discovery platform uses patterned arrays coupled with electrochemiluminescence to simultaneously measure single or multiple biomarkers in a single run with increased sensitivity. Samples were analyzed on a single lot of reagents, and the assay was validated in-house before use. All samples were assayed in singlet, and a subset of samples were assayed in duplicate to assess interassay and intra-assay coefficient of variation. The interassay and intra-assay coefficients of variation were 4.6% and 0.9%, respectively. All samples were analyzed on the same lot of reagents to avoid any batch bias. In addition, 2 quality control samples were analyzed on each plate to assess run acceptability and assay drift. Levy-Jennings plots were constructed, and acceptability was determined using 22S and 13S rules. The primary outcome of MAKEs in this study was a composite of CKD incidence in participants with baseline eGFR ≥60 ml/min per 1.73 m2, CKD progression in participants with baseline eGFR <60 ml/min per 1.73 m2, or development of end-stage kidney disease (ESKD).20Hsu C.Y. Chinchilli V.M. Coca S. et al.Post-acute kidney injury proteinuria and subsequent kidney disease progression: the Assessment, Serial Evaluation, and Subsequent Sequelae in Acute Kidney Injury (ASSESS-AKI) Study.JAMA Intern Med. 2020; 180: 402-410Crossref PubMed Scopus (85) Google Scholar Specifically, CKD incidence was defined as experiencing ≥25% reduction in eGFR in addition to an overall decline in eGFR of <60 ml/min per 1.73 m2. CKD progression was defined as experiencing ≥50% reduction in eGFR, or an overall decline in eGFR of <15 ml/min per 1.73 m2. ESKD was defined as requiring dialysis treatment at least once a week for ≥12 consecutive weeks, receipt of a kidney transplant, or death while receiving dialysis. The time to the primary outcome of MAKEs was censored at the time of death or last study follow-up visit. To complement the investigation of uEGF/Cr over time with MAKEs and inform the AKI-to-CKD transition, we used quantitative polymerase chain reaction analysis and single-cell RNA sequencing in 2 mouse models of IRI in the kidney we have recently characterized in detail.13Puthumana J. Thiessen-Philbrook H. Xu L. et al.Biomarkers of inflammation and repair in kidney disease progression.J Clin Invest. 2021; 131e139927Crossref PubMed Scopus (75) Google Scholar,22Xu L. Guo J. Moledina D.G. et al.Immune-mediated tubule atrophy promotes acute kidney injury to chronic kidney disease transition.Nat Commun. 2022; 13: 4892Crossref PubMed Scopus (18) Google Scholar,23Wen Y. Xu L. Melchinger I.A. et al.Longitudinal biomarkers and kidney disease progression after acute kidney injury.JCI Insight. 2023; 8e167731Crossref Scopus (6) Google Scholar Comparing a model of adaptive repair with one of progressive atrophy after IRI,22Xu L. Guo J. Moledina D.G. et al.Immune-mediated tubule atrophy promotes acute kidney injury to chronic kidney disease transition.Nat Commun. 2022; 13: 4892Crossref PubMed Scopus (18) Google Scholar we examined gene expression kinetics over time and across specific kidney cell types. All animal protocols were approved by the Yale University Institutional Animal Care and Use Committee (protocol number 10538). Additional details can be found in the Supplementary Methods. We summarized descriptive characteristics using mean ± SD or median (interquartile range) for continuous variables, and we calculated frequency (percentage) for categorical variables. uEGF levels during hospitalization and at 3-month follow-up were modeled after normalization to urinary creatinine concentration and log2 transformation for both continuous and categorical analyses. The difference in uEGF/Cr from hospitalization to the 3-month postdischarge time point was calculated by subtracting the uEGF/Cr level at hospitalization from the level at 3 months. Multivariable Cox proportional hazards regression was used to evaluate the association of uEGF/Cr at 3 months postdischarge with MAKEs. Model 1 evaluated risk of MAKEs by uEGF/Cr in unadjusted analysis. Model 2 adjusted for demographic factors (sex, race, and ethnicity), baseline medical comorbidities (smoking status, diabetes mellitus, hypertension, congestive heart failure, cardiovascular disease, and sepsis during hospitalization), 3-month urine albumin measurement, BMI, and the difference in eGFR from hospitalization to 3-month follow-up. Model 3 further adjusted for urinary biomarkers of kidney injury, inflammation, and repair at 3-month follow-up (neutrophil gelatinase-associated lipocalin, interleukin-18, kidney injury molecule-1, monocyte chemoattractant protein-1, uromodulin, and chitinase 3–like protein 1). We also investigated the association of uEGF/Cr measured at hospitalization with MAKEs. For this analysis, we similarly adjusted for demographic factors, baseline comorbidities, and the following variables at the time of hospitalization: eGFR, urine albumin, and urinary biomarkers. We additionally performed stratified analysis by AKI status at the time of hospitalization (no AKI, stage 1, and stage 2/3). We next investigated the association between the change in uEGF/Cr with MAKEs in categorical analysis by tertile. Participants in tertile 1 had a decline in uEGF/Cr from hospitalization to 3-month follow-up, whereas participants in tertile 3 had an increase in uEGF/Cr from hospitalization to 3-month follow-up and participants in tertile 2 had the least amount of change in uEGF/Cr level. Risk of MAKEs for participants with either an increase or a decrease in uEGF/Cr was evaluated, with tertile 2 as reference. In model 1, we adjusted only for uEGF/Cr level at hospitalization. We then adjusted for eGFR change from hospitalization to 3-month follow-up, demographic factors, and other urinary biomarkers at 3 months (models 2 and 3). We performed stratified analysis evaluating uEGF/Cr change with MAKEs by AKI status. Graphical analyses and correlation tests of scaled Schoenfeld residuals were used to evaluate proportional hazards assumptions for all Cox models. We performed a supplementary analysis evaluating the overall event rate of ESKD (a subset of the primary composite outcome) by quartile of uEGF/Cr level at both time points. We used random intercept mixed models to evaluate the percentage change in eGFR per year for uEGF/Cr quartiles at hospitalization, uEGF/Cr quartiles at 3-month follow-up, and tertiles of change in uEGF/Cr. Fixed effects included eGFR, demographic factors, baseline medical comorbidities, urine albumin, and BMI. We performed additional analyses for uEGF/Cr at 3 months, uEGF/Cr at hospitalization, and the change from hospitalization to 3-month follow-up using death as a competing risk by the Fine and Gray method. The observation window for all of our Cox models started at the time of 3-month postdischarge follow-up. To quantify clinical discrimination, we calculated area under the receiver-operating characteristic curve (AUC) at 4 years (closest to the median follow-up time), for a univariate model of uEGF/Cr, a model containing clinical variables alone, and combined models including clinical variables and other urinary biomarkers at 3 months after hospital discharge. To evaluate if uEGF/Cr improved prediction performance beyond clinical variables, we examined the uEGF/Cr regression coefficient from Cox models.24Pepe M.S. Kerr K.F. Longton G. et al.Testing for improvement in prediction model performance.Stat Med. 2013; 32: 1467-1482Crossref PubMed Scopus (169) Google Scholar All analyses were performed in SAS, version 9.4 (SAS Institute), Prism 8 (GraphPad Software), and R, version 3.1.2 for statistical analysis (R Foundation for Statistical Computing). All tests of statistical significance were 2 sided, with P < 0.05 considered significant. The study was approved by the institutional review boards at each participating site of the ASSESS-AKI Study, and written informed consent was obtained from all participants. Participants had a mean age of 64.6 ± 12.6 years, with 37% of the population women and 13% Black race (Table 1). Those in the highest quartile of uEGF/Cr at 3-month postdischarge follow-up had a lower prevalence of diabetes mellitus, hypertension, congestive heart failure, and cardiovascular disease compared with those in the lower quartiles of uEGF/Cr. Similarly, participants in the highest quartile also had a higher preadmission eGFR compared with other quartiles. Over the course of hospitalization, participants in the highest quartile also had a lower incidence of AKI (31%), with most AKI seen across all quartiles being mild, KDIGO stage 1. A total of 299 (20%) participants developed MAKEs at a median of 4.3 years of follow-up, with a median event rate of 47.2 (95% confidence interval [CI], 42.1–52.9) events per 1000 person-years (py).Table 1Clinical characteristics by uEGF/Cr quartile at 3-month follow-upVariableOverallUrine EGF/Cr quartile at 3-mo follow-up (ng/mg)Quartile 1 (n = 374) (0.20–2.50)Quartile 2 (n = 378) (2.51–4.16)Quartile 3 (n = 381) (4.17–6.34)Quartile 4 (n = 376) (6.36–31.0)Characteristics at baseline Age, yr64.6 ± 12.666.9 ± 11.568.1 ± 10.264.1 ± 12.059.4 ± 14.7 Sex, female566 (37)125 (33)134 (35)124 (32)183 (48) Black race201 (13)82 (22)59 (16)31 (8)29 (8) Diabetes648 (43)246 (65)178 (47)143 (37)81 (21) Hypertension1133 (75)326 (86)313 (83)286 (75)208 (55) Congestive heart failure322 (21)123 (33)85 (22)78 (20)36 (9) Cardiovascular disease686 (45)209 (55)187 (49)169 (44)121 (32) CKD601 (40)288 (76)201 (53)77 (20)35 (9) Preadmission serum creatinine, mg/dl1.2 ± 0.51.6 ± 0.71.2 ± 0.31.0 ± 0.30.9 ± 0.2 Preadmission eGFR, ml/min per 1.73 m268.8 ± 25.048.4 ± 22.261.4 ± 17.576.9 ± 19.688.3 ± 20.2Characteristics at time of hospitalization Alb/Cr, mg/g32.0 (12.5–88.3)70.4 (23.8–273.0)35.2 (13.3–77.0)25.6 (10.4–66.0)20.7 (9.4–61.8) Alb/Cr range, mg<30734 (48)118 (31)169 (45)217 (57)230 (61)30–300623 (41)170 (45)172 (45)149 (39)132 (35)>300161 (11)89 (24)38 (10)16 (4)18 (5) AKI760 (50)252 (67)211 (56)179 (47)118 (31) Stage 1 AKI547 (36)185 (49)149 (39)131 (34)82 (22) Stage 2 AKI117 (8)30 (8)37 (10)26 (7)24 (6) Stage 3 AKI96 (6)37 (10)25 (7)22 (6)12 (3) ICU admission1008 (66)238 (63)240 (63)265 (69)265 (70) Receipt of mechanical ventilation65 (4)18 (5)20 (5)14 (4)13 (3) Receipt of vasopressors or inotropes480 (32)103 (27)148 (39)123 (32)106 (28)Characteristics at 3-mo posthospitalization discharge follow-up BMI, kg/m231.0 ± 7.731.9 ± 8.131.8 ± 7.731.0 ± 7.429.4 ± 7.2 Serum creatinine, mg/dl1.2 ± 0.61.7 ± 0.91.2 ± 0.31.0 ± 0.20.8 ± 0.2 eGFR, ml/min per 1.73 m269.2 ± 25.746.1 ± 20.862.6 ± 17.777.0 ± 20.190.8 ± 19.7 Alb/Cr, mg/g14.4 (6.7–57.9)48.1 (14.4–491.1)17.1 (7.6–63.9)9.8 (5.3–26.1)9.3 (6.0–20.0)AKI, acute kidney injury; Alb/Cr, albumin-to-creatinine ratio; BMI, body mass index; CKD, chronic kidney disease; Cr, creatinine; eGFR, estimated glomerular filtration rate; ICU, intensive care unit; IQR, interquartile range; uEGF, urinary epidermal growth factor.Values are reported as mean ± SD, n (%), or median (IQR). Open table in a new tab AKI, acute kidney injury; Alb/Cr, albumin-to-creatinine ratio; BMI, body mass index; CKD, chronic kidney disease; Cr, creatinine; eGFR, estimated glomerular filtration rate; ICU, intensive care unit; IQR, interquartile range; uEGF, urinary epidermal growth factor. Values are reported as mean ± SD, n (%), or median (IQR). Participants in the highest quartile of uEGF/Cr at 3 months had the lowest cumulative incidence of MAKEs (Figure 1a). Furthermore, participants in the highest quartile had a mean decline of 2.3% in eGFR per year, compared with 5.6% eGFR decline per year in those in the lowest quartile (Figure 2a). Participants in the lowest quartile of uEGF/Cr level had the highest event rate (93.1/1000 py), compared with those in the highest quartile (20.4/1000 py; Table 2). Each 2-fold higher uEGF/Cr level measured at 3-month follow-up was associated with decreased risk of MAKEs in unadjusted analysis (hazard ratio [HR], 0.35; 95% CI